Shoaib Hassan^1,*, Qianmu Li^1,*, Muhammad Zubair², Rakan A. Alsowail³, Muhammad Umair²

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4041-4067, 2025, DOI:10.32604/cmc.2025.059832 - 06 March 2025

Abstract As the trend to use the latest machine learning models to automate requirements engineering processes continues, security requirements classification is tuning into the most researched field in the software engineering community. Previous literature studies have proposed numerous models for the classification of security requirements. However, adopting those models is constrained due to the lack of essential datasets permitting the repetition and generalization of studies employing more advanced machine learning algorithms. Moreover, most of the researchers focus only on the classification of requirements with security keywords. They did not consider other nonfunctional requirements (NFR) directly or… More >

Haydar Abdulameer Marhoon^1,2,*, Rafid Sagban^3,4, Atheer Y. Oudah^1,5, Saadaldeen Rashid Ahmed^6,7

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4181-4218, 2025, DOI:10.32604/cmc.2025.058822 - 06 March 2025

Abstract In order to address the critical security challenges inherent to Wireless Sensor Networks (WSNs), this paper presents a groundbreaking barrier-based machine learning technique. Vital applications like military operations, healthcare monitoring, and environmental surveillance increasingly deploy WSNs, recognizing the critical importance of effective intrusion detection in protecting sensitive data and maintaining operational integrity. The proposed method innovatively partitions the network into logical segments or virtual barriers, allowing for targeted monitoring and data collection that aligns with specific traffic patterns. This approach not only improves the diversit. There are more types of data in the training set,… More >

Jian Gao¹, Hongliang Hao², Caifeng Wen^1,*, Yongsheng Wang³, Zhanhua Han⁴, Edwin E. Nykilla², Yuwen Zhang²

Energy Engineering, Vol.122, No.3, pp. 1175-1198, 2025, DOI:10.32604/ee.2025.061083 - 07 March 2025

Abstract Power quality is a crucial area of research in contemporary power systems, particularly given the rapid proliferation of intermittent renewable energy sources such as wind power. This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra, PSD, and random signal power spectra. The relationship was derived, validated through experiments and simulations, and subsequently applied to multi-objective optimization. Various optimization algorithms were compared to achieve optimal system power quality. The findings revealed that the relationships between power quality indices and PSD were influenced by variations in More >

Yu Zhang^*, Sheng Wang, Fanming Zeng, Yijie Lin

Energy Engineering, Vol.122, No.3, pp. 1137-1151, 2025, DOI:10.32604/ee.2025.060945 - 07 March 2025

Abstract With the development of renewable energy technologies such as photovoltaics and wind power, it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement. To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy, while simultaneously enhancing user satisfaction on the demand side, this paper introduces an improved multi-objective Grey Wolf Optimizer based on Cauchy variation. The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of… More > Graphic Abstract

Chenxu Wang^*, Jing Bian, Rui Yuan

Energy Engineering, Vol.122, No.3, pp. 985-1003, 2025, DOI:10.32604/ee.2025.059559 - 07 March 2025

Abstract Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load, a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed. Firstly, the k-medoids clustering algorithm is used to divide the reduced power scene into periods. Then, the discrete variables and continuous variables are optimized in the same period of time. Finally, the number of input groups of parallel capacitor banks (CB) in multiple periods is fixed, and then the secondary static reactive power optimization correction is carried out by… More >

Digambar Singh¹, Najat Elgeberi², Mohammad Aljaidi^3,*, Ramesh Kumar^4,5, Rabia Emhamed Al Mamlook⁶, Manish Kumar Singla^4,7,8,*

Energy Engineering, Vol.122, No.3, pp. 823-859, 2025, DOI:10.32604/ee.2025.059309 - 07 March 2025

Abstract The literature on multi-attribute optimization for renewable energy source (RES) placement in deregulated power markets is extensive and diverse in methodology. This study focuses on the most relevant publications directly addressing the research problem at hand. Similarly, while the body of work on optimal location and sizing of renewable energy generators (REGs) in balanced distribution systems is substantial, only the most pertinent sources are cited, aligning closely with the study’s objective function. A comprehensive literature review reveals several key research areas: RES integration, RES-related optimization techniques, strategic placement of wind and solar generation, and RES… More >

Ahmed Mohamed Galal^1,2, Adebowale Martins Obalalu³, Akintayo Oladimeji Akindele⁴, Umair Khan^5,6, Abdulazeez Adebayo Usman⁷, Olalekan Adebayo Olayemi⁸, Najiyah Safwa Khashi’ie^9,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3089-3113, 2025, DOI:10.32604/cmes.2025.061296 - 03 March 2025

Abstract The need for efficient thermal energy systems has gained significant attention due to the growing global concern about renewable energy resources, particularly in residential buildings. One of the biggest challenges in this area is capturing and converting solar energy at maximum efficiency. This requires the use of strong materials and advanced fluids to enhance conversion efficiency while minimizing energy losses. Despite extensive research on thermal energy systems, there remains a limited understanding of how the combined effects of thermal radiation, irreversibility processes, and advanced heat flux models contribute to optimizing solar power performance in residential… More > Graphic Abstract

G. Sukanya, J. Priyadarshini^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2925-2958, 2025, DOI:10.32604/cmes.2025.060030 - 03 March 2025

Abstract Advancements in Natural Language Processing and Deep Learning techniques have significantly propelled the automation of Legal Judgment Prediction, achieving remarkable progress in legal research. Most of the existing research works on Legal Judgment Prediction (LJP) use traditional optimization algorithms in deep learning techniques falling into local optimization. This research article focuses on using the modified Pelican Optimization method which mimics the collective behavior of Pelicans in the exploration and exploitation phase during cooperative food searching. Typically, the selection of search agents within a boundary is done randomly, which increases the time required to achieve global… More >

Hongkun Lu^1,2,*, M. M. Noor^2,3,4,*, K. Kadirgama²

Frontiers in Heat and Mass Transfer, Vol.23, No.1, pp. 299-324, 2025, DOI:10.32604/fhmt.2024.059871 - 26 February 2025

Abstract To improve the thermal performance and temperature uniformity of battery pack, this paper presents a novel battery thermal management system (BTMS) that integrates oscillating heat pipe (OHP) technology with liquid cooling. The primary innovation of the new hybrid BTMS lies in the use of an OHP with vertically arranged evaporator and condenser, enabling dual heat transfer pathways through liquid cooling plate and OHP. This study experimentally investigates the performance characteristics of the ⊥-shaped OHP and hybrid BTMS. Results show that lower filling ratios significantly enhance the OHP’s startup performance but reduce operational stability, with optimal… More >

Amjad Khan¹, Rahim Khan^1,*, Fahad Alturise^2,*, Tamim Alkhalifah³

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3161-3178, 2025, DOI:10.32604/cmc.2025.060372 - 17 February 2025

Abstract The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the… More >